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Record W4310817944 · doi:10.1177/14639491221139314

Encounters with public art in teacher education: Timely pedagogies disrupting colonial relations with place

2022· article· en· W4310817944 on OpenAlexaffabout
Elaine de Fatima Beltran-Sellitti, Tahmina Shayan

Bibliographic record

VenueContemporary Issues in Early Childhood · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsCapilano University
Fundersnot available
KeywordsSociologySubjectivityRelation (database)ColonialismVisual arts educationIndigenousPedagogyPositivismAestheticsVisual artsEpistemologyPolitical scienceArtLawThe arts

Abstract

fetched live from OpenAlex

Public art is placed in relation to its surroundings, conveying messages that are open to interpretation and thus proposing conversations between art/aesthetics, geography, histories and the subjectivity of the viewer. As such, it can engender possibilities to ‘politicize our relations with place’. Embracing the vision of a multidisciplinary assignment for an introductory course on place relations for first-year students in a Canadian teaching university, the authors designed an assignment of living inquiry with public art. The students placed themselves in relation to the art piece by studying the surrounding area of the artwork, embracing the propositions of the piece, and responding to those propositions artistically and through writing. What does it mean to live on Indigenous land? It was imperative to introduce conversations about the different but interconnected concepts of place and land that house public art pieces. The authors envisioned teacher education beyond the limits of a positivist dominant developmental lens that constrains holistic and critical possibilities to embrace decolonial acts. They asked: How might pre-service education disrupt the colonial inheritance and practices rooted in early childhood education? The students critically reflected on their geopolitical position, the contemporary issues of our time and the implications for their journey of becoming educators.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.421
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.288
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes2
Has abstractyes

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